Universität Bern · Education
PhD Position in Mathematical Foundations of Machine Learning
UniBE is ambitious.
With us, you deliver top performance and test your skills against the best. You will join an active, supportive, inclusive, and collaborative research environment at the Department of Mathematics and Statistics. You will work on exciting fundamental questions at the interface of mathematics and modern AI and collaborate with national and international researchers. You will also contribute to teaching as a teaching assistant.
Employment conditions and remuneration are in accordance with the standards of the University of Bern, Switzerland. Applicants should hold, or be close to completing, a Master's degree in pure or applied mathematics, theoretical physics, statistics, or a related field.
We seek motivated candidates with a strong background in mathematics (e.g., in one or more of the following areas: analysis, probability theory, stochastic processes, statistical physics, optimal transport, dynamical systems, optimization, or machine learning theory), an interest in the mathematical principles underlying modern AI (or in related problems), the ability to work both independently and collaboratively, and good written and spoken English. Knowledge of German is not required. Programming experience is beneficial but not required. International reputation
With us, you deliver top performance and test your skills against the best. You will join an active, supportive, inclusive, and collaborative research environment at the Department of Mathematics and Statistics. You will work on exciting fundamental questions at the interface of mathematics and modern AI and collaborate with national and international researchers. You will also contribute to teaching as a teaching assistant.
Employment conditions and remuneration are in accordance with the standards of the University of Bern, Switzerland. Applicants should hold, or be close to completing, a Master's degree in pure or applied mathematics, theoretical physics, statistics, or a related field.
We seek motivated candidates with a strong background in mathematics (e.g., in one or more of the following areas: analysis, probability theory, stochastic processes, statistical physics, optimal transport, dynamical systems, optimization, or machine learning theory), an interest in the mathematical principles underlying modern AI (or in related problems), the ability to work both independently and collaboratively, and good written and spoken English. Knowledge of German is not required. Programming experience is beneficial but not required. International reputation